Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/24319
Title: Two-step similarity matching for content-Based video retrieval in P2P, networks
Authors: Niu, J
Wang, Z
Feng, D
Keywords: Content-Based Video Retrieval (CBVR)
Peer-to-Peer (P2P) networks
Similarity matching
Issue Date: 2010
Publisher: IEEE
Source: 2010 IEEE International Conference on Multimedia and Expo (ICME), 19-23 July 2010, Suntec City, p. 1690-1694 How to cite?
Abstract: Multimedia data, particularly, video data, has dominated peer-to-peer (P2P) networks. Therefore, it is demanding to provide content based retrieval in P2P networks. Similarity matching is one of the challenging issues. In this paper, we present a novel two-step method to reduce computational complexity of similarity matching in P2P networks. In the first step, an efficient maximum matching (MM) technique is employed to obtain an initial set of similar video candidates. In the second step, these candidates are further selected with a more accurate, but more computationally expensive optimal matching (OM) technique. In order to further improve the computational efficiency of the proposed method, four other matching techniques are proposed to replace MM technique. Various experimental results indicate that the proposed approach is more effective for CBVR while achieving significantly computational saving.
URI: http://hdl.handle.net/10397/24319
ISBN: 978-1-4244-7491-2
ISSN: 1945-7871
DOI: 10.1109/ICME.2010.5582942
Appears in Collections:Conference Paper

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